Faculty Bibliography

BACKGROUND:Sublingual buprenorphine-naloxone (BUP-NX), an FDA-approved treatment for opioid use disorder (OUD), combines buprenorphine (a partial mu/kappa agonist) with naloxone (a mu/ kappa antagonist). Extended-release injection naltrexone (XR-NTX; a mu receptor antagonist and kappa receptor partial agonist) is also an FDA-approved treatment for OUD. However, while some patients respond well to these medications, many others leave treatment and relapse. OBJECTIVES/OBJECTIVE:Determine whether gene variants in the opioid gene system are associated with better or worse treatment response. METHODS:= 334), two outcomes measures were assessed: received first dose (yes/no) and received last dose (yes/no). Separate logistic regressions were used to each model outcome measure as a function of treatment (XR-NTX vs BUP-NX), each gene variant, and their interaction. RESULTS:There were no significant main effects of gene variant on receiving first dose or last dose. There were also no significant gene variant by treatment interactions. CONCLUSIONS:The outcome of treatment of OUD with medications is likely a complex function of multiple factors, including environmental, psychosocial, and possibly genetic, such that major effects of genetic variants may be unlikely.

Here we review the impact of obstructive sleep apnea (OSA) on biomarkers of Alzheimer's disease (AD) pathogenesis, neuroanatomy, cognition and neurophysiology, and present the research investigating the effects of continuous positive airway pressure (CPAP) therapy. OSA is associated with an increase in AD markers amyloid-β and tau measured in cerebrospinal fluid (CSF), by Positron Emission Tomography (PET) and in blood serum. There is some evidence suggesting CPAP therapy normalizes AD biomarkers in CSF but since mechanisms for amyloid-β and tau production/clearance in humans are not completely understood, these findings remain preliminary. Deficits in the cognitive domains of attention, vigilance, memory and executive functioning are observed in OSA patients with the magnitude of impairment appearing stronger in younger people from clinical settings than in older community samples. Cognition improves with varying degrees after CPAP use, with the greatest effect seen for attention in middle age adults with more severe OSA and sleepiness. Paradigms in which encoding and retrieval of information are separated by periods of sleep with or without OSA have been done only rarely, but perhaps offer a better chance to understand cognitive effects of OSA than isolated daytime testing. In cognitively normal individuals, changes in EEG microstructure during sleep, particularly slow oscillations and spindles, are associated with biomarkers of AD, and measures of cognition and memory. Similar changes in EEG activity are reported in AD and OSA, such as "EEG slowing" during wake and REM sleep, and a degradation of NREM EEG microstructure. There is evidence that CPAP therapy partially reverses these changes but large longitudinal studies demonstrating this are lacking. A diagnostic definition of OSA relying solely on the Apnea Hypopnea Index (AHI) does not assist in understanding the high degree of inter-individual variation in daytime impairments related to OSA or response to CPAP therapy. We conclude by discussing conceptual challenges to a clinical trial of OSA treatment for AD prevention, including inclusion criteria for age, OSA severity, and associated symptoms, the need for a potentially long trial, defining relevant primary outcomes, and which treatments to target to optimize treatment adherence.

Using objectively-measured height and weight data from academic years 2009-2013 (n = 1,114,010 student-year observations), we estimated the association between the food outlet in closest proximity to schools and the likelihood of obesity among New York City public high school students. Obesity risk was higher for students with a corner store as the nearest option to schools, regardless of whether other food outlet types were located within a quarter mile or a half mile of schools (i.e., benchmarks for zoning policies). Policymakers may want to consider introducing healthier food options near schools, in conjunction with programs to support changes within corner stores.

There has been a substantial rise in the number of women pursuing careers in neurology. However, research has shown that women in neurology have high rates of burnout with gender disparities in burnout and attrition in the field. Recently, there was a call from the NIH, including the National Institute of Neurological Disorders and Stroke, asking for input on factors that may limit or discourage grant applications from women. As the recipients of the highly coveted NIH career mentored awards (K awards) in headache medicine, we applaud the NIH for asking for gender-specific feedback and for raising awareness of research showing that female faculty on the Research Track are at an increased risk of departure. Using the NIH model for the Responsible Conduct of Research and the tenant of Nurturing the Fertile Environment, we discuss specific challenges in academic research that may contribute to gender differences in neurology research success. Although the rate of women conducting NIH-funded migraine research increased from 23% to 41% over the last 10 years, more women are currently in training compared with independence, with 6/6 of the NIH training grants but only 12/36 of the NIH research-level grants, held by women in fiscal years 2017-2019. We suggest concrete solutions to these challenges to ensure the success of women in research reaching independence.

Outdoor air pollution is a major contributor to the burden of disease worldwide. Most of the global population resides in places where air pollution levels, because of emissions from industry, power generation, transportation, and domestic burning, considerably exceed the World Health Organization's health-based air-quality guidelines. Outdoor air pollution poses an urgent worldwide public health challenge because it is ubiquitous and has numerous serious adverse human health effects, including cancer. Currently, there is substantial evidence from studies of humans and experimental animals as well as mechanistic evidence to support a causal link between outdoor (ambient) air pollution, and especially particulate matter (PM) in outdoor air, with lung cancer incidence and mortality. It is estimated that hundreds of thousands of lung cancer deaths annually worldwide are attributable to PM air pollution. Epidemiological evidence on outdoor air pollution and the risk of other types of cancer, such as bladder cancer or breast cancer, is more limited. Outdoor air pollution may also be associated with poorer cancer survival, although further research is needed. This report presents an overview of outdoor air pollutants, sources, and global levels, as well as a description of epidemiological evidence linking outdoor air pollution with cancer incidence and mortality. Biological mechanisms of air pollution-derived carcinogenesis are also described. This report concludes by summarizing public health/policy recommendations, including multilevel interventions aimed at individual, community, and regional scales. Specific roles for medical and health care communities with regard to prevention and advocacy and recommendations for further research are also described.

INTRODUCTION/BACKGROUND:Qualitative analysis of Twitter posts reveals key insights about user norms, informedness, perceptions, and experiences related to opioid use disorder (OUD). This paper characterizes Twitter message content pertaining to medications for opioid use disorder (MOUD) and Naloxone. METHODS:In-depth thematic analysis was conducted of 1,010 Twitter messages collected in June 2019. Our primary aim was to identify user perceptions and experiences related to harm reduction (e.g., Naloxone) and MOUD (e.g., sublingual and Extended-release buprenorphine, Extended-release naltrexone, Methadone). RESULTS:Tweets relating to OUD were most commonly authored by general Twitter users (43.8%), private residential or detoxification programs (24.6%), healthcare providers (e.g., physicians, first responders; 4.3%), PWUOs (4.7%) and their caregivers (2.9%). Naloxone was mentioned in 23.8% of posts and authored most commonly by general users (52.9%), public health experts (7.4%), and nonprofit/advocacy organizations (6.6%). Sentiment was mostly positive about Naloxone (73.6%). Commonly mentioned MOUDs in our search consisted of Buprenorphine-naloxone (13.8%), Methadone (5.7%), Extended-release naltrexone (4.1%), and Extended-release buprenorphine (0.01%). Tweets authored by PWUOs (4.7%) most commonly related to factors influencing access to MOUD or adverse events related to MOUD (70.8%), negative or positive experiences with illicit substance use (25%), policies related to expanding access to treatments for OUD (8.3%), and stigma experienced by healthcare providers (8.3%). CONCLUSION/CONCLUSIONS:Twitter is utilized by a diverse array of individuals, including PWUOs, and offers an innovative approach to evaluate experiences and themes related to illicit opioid use, MOUD, and harm reduction.

BACKGROUND:The COVID-19 pandemic has resulted in significant morbidity and mortality, with large numbers of patients requiring intensive care threatening to overwhelm healthcare systems globally. There is an urgent need for a COVID-19 disease severity assessment that can assist in patient triage and resource allocation for patients at risk for severe disease. OBJECTIVE:The goal of this study was to develop, validate, and scale a clinical decision support system and mobile app to assist in COVID-19 severity assessment, management, and care. METHODS:Model training data from 701 patients with COVID-19 were collected across practices within the Family Health Centers network at New York University Langone Health. A two-tiered model was developed. Tier 1 uses easily available, non-laboratory data to help determine whether biomarker-based testing and/or hospitalization is necessary. Tier 2 predicts probability of mortality using biomarker measurements (CRP, PCT, D-dimer) and age. Both Tier 1 and Tier 2 models were validated using two external datasets from hospitals in Wuhan, China comprising 160 and 375 patients, respectively. RESULTS:All biomarkers were measured at significantly higher levels in patients that died vs. those that were not hospitalized or discharged (P < .001). The Tier 1 and Tier 2 internal validation had AUC (95% confidence interval) of 0.79 (0.74-0.84) and 0.95 (0.92-0.98), respectively. The Tier 1 and Tier 2 external validation had AUCs of 0.79 (0.74-0.84) and 0.97 (0.95-0.99), respectively. CONCLUSIONS:Our results demonstrate validity of the clinical decision support system and mobile app, which are now ready to assist healthcare providers in making evidence-based decisions in managing COVID-19 patient care. The deployment of these new capabilities has potential for immediate impact in community clinics, sites whereby application of such tools could lead to improvements in patient outcomes and cost containment. CLINICALTRIAL/UNASSIGNED/:

INTRODUCTION/BACKGROUND:People with serious mental illness (SMI) have a high smoking prevalence and low quit rates. Few cessation treatments are tested in smokers with SMI. Mental health (MH) providers are reluctant to address smoking. Proactive tobacco cessation treatment strategies reach out directly to smokers to offer counseling and medication and improve treatment utilization and quit rates. The current study is a secondary analysis of a randomized controlled trial of proactive outreach for tobacco cessation treatment in VA MH patients. METHODS:Participants (N=1938, 83% male, mean age 55.7) across 4 recruitment sites, who were current smokers and had a MH visit in the past 12 months, were identified using the electronic medical record. Participants were randomized to Intervention (telephone outreach call plus invitation to engage in MH tailored telephone counseling and assistance obtaining nicotine replacement therapy [NRT]) or Control (usual care). The current study assessed outcomes in participants with SMI (N=982). RESULTS:Compared to the Control group, participants assigned to the Intervention group were more likely to engage in telephone counseling (22% vs. 3%) and use NRT (51% vs. 41%). Participants in the Intervention group were more likely to be abstinent (7-day point prevalence; 18%) at 12 months than participants in the Control group; 11%) but equally likely to make quit attempts. CONCLUSIONS:Proactive tobacco cessation treatment is an effective strategy for tobacco users with SMI. Proactive outreach had a particularly strong effect on counseling utilization. Future randomized clinical trials examining proactive tobacco treatment approaches in SMI treatment settings are needed. IMPLICATIONS/CONCLUSIONS:Few effective treatment models exist for smokers with serious mental illness. Proactive tobacco cessation outreach with connections to mental health tailored telephone counseling and medication promotes tobacco abstinence among smokers with serious mental illness and is an effective treatment strategy for this underserved population.

BACKGROUND:It is important to monitor the scope of clinical research of all types, to involve participants of all ages and subgroups in studies that are appropriate to their condition, and to ensure equal access and broad validity of the findings. OBJECTIVE:We conducted a review of clinical research performed at New York University with the following objectives: (1) to determine the utility of institutional administrative data to characterize clinical research activity; (2) to assess the inclusion of special populations; and (3) to determine if the type, initiation, and completion of the study differed by age. METHODS:Data for all studies that were institutional review board-approved between January 1, 2014, and November 2, 2016, were obtained from the research navigator system, which was launched in November 2013. One module provided details about the study protocol, and another module provided the characteristics of individual participants. Research studies were classified as observational or interventional. Descriptive statistics were used to assess the characteristics of clinical studies across the lifespan, by type, and over time. RESULTS:A total of 22%-24% of studies included children (minimum age <18 years) and 4%-5% focused exclusively on pediatrics. Similarly, 64%-72% of studies included older patients (maximum age >65 years) but only 5%-12% focused exclusively on geriatrics. Approximately 85% of the studies included both male and female participants. Of the remaining studies, those open only to girls or women were approximately 3 times as common as those confined to boys or men. A total of 56%-58% of projects focused on nonvulnerable patients. Among the special populations studied, children (12%-15%) were the most common. Noninterventional trial types included research on human data sets (24%), observational research (22%), survey research (16%), and biospecimen research (8%). The percentage of projects designed to test an intervention in a vulnerable population increased from 17% in 2014 to 21% in 2015. CONCLUSIONS:Pediatric participants were the special population that was most often studied based on the number of registered projects that included children and adolescents. However, they were much less likely to be successfully enrolled in research studies compared with adults older than 65 years. Only 20% of the studies were interventional, and 20%-35% of participants in this category were from vulnerable populations. More studies are exclusively devoted to women's health issues compared with men's health issues.